Transferring Tactile Data Across Sensors

TL;DR

This paper presents a novel method for translating tactile data between sensors by leveraging deformation information, enabling reuse of datasets despite sensor deprecation, demonstrated through translating BioTac signals into DIGIT sensor data.

Contribution

The paper introduces a deformation-based translation framework for tactile sensors, allowing data transfer without relying on output signals, which is a novel approach in tactile data processing.

Findings

Successfully translated BioTac data into DIGIT sensor signals

Preserved tactile information across different sensor types

Enabled reuse of existing tactile datasets

Abstract

Tactile perception is essential for human interaction with the environment and is becoming increasingly crucial in robotics. Tactile sensors like the BioTac mimic human fingertips and provide detailed interaction data. Despite its utility in applications like slip detection and object identification, this sensor is now deprecated, making many existing datasets obsolete. This article introduces a novel method for translating data between tactile sensors by exploiting sensor deformation information rather than output signals. We demonstrate the approach by translating BioTac signals into the DIGIT sensor. Our framework consists of three steps: first, converting signal data into corresponding 3D deformation meshes; second, translating these 3D deformation meshes from one sensor to another; and third, generating output images using the converted meshes. Our approach enables the continued use of valuable datasets.